HiddenPromptsPlanos de prompts probados para resultados fiables.
ES
English Español Português Deutsch Français 日本語 한국어 हिन्दी العربية Bahasa Indonesia
Volver a la galería

Programación

PHP Debugging Investigation

Diagnose a PHP failure with ranked hypotheses, safe checks, and a minimal repair path.

Modelos
DeepSeek, ChatGPT
Nivel
Avanzado
Versión
v0.9

Este prompt está disponible actualmente en inglés. La interfaz permanece en el idioma elegido.

01

Qué hace

Diagnose a PHP failure with ranked hypotheses, safe checks, and a minimal repair path.

02

Ideal para

Symptom summary, likely causes ranked by evidence, verification commands, minimal patch, regression checks, and rollback note.

03

Variables

[ERROR][CODE][ENVIRONMENT][EXPECTED_BEHAVIOR]
Prompt del sistema
You are a senior PHP production engineer. Diagnose before changing code and do not invent runtime evidence.
Prompt del usuario
OBJECTIVE:
Investigate [ERROR] in [CODE] running in [ENVIRONMENT]. Expected behavior: [EXPECTED_BEHAVIOR].

INPUTS:
ERROR: [ERROR]
CODE: [CODE]
ENVIRONMENT: [ENVIRONMENT]
EXPECTED_BEHAVIOR: [EXPECTED_BEHAVIOR]

OUTPUT CONTRACT:
Symptom summary, likely causes ranked by evidence, verification commands, minimal patch, regression checks, and rollback note.

Cómo usarlo

Replace every variable with specific, non-sensitive information. Remove irrelevant sections and add one representative example when tone or classification matters.

Por qué funciona

The blueprint separates authority, task context, evidence limits, and the output contract so requirements can be checked independently.

Compatibilidad

ChatGPTuntestedEditorial compatibility hypothesis; cross-model test record pending.

DeepSeekuntestedEditorial compatibility hypothesis; cross-model test record pending.

05

Entrada de ejemplo

ERROR: [ERROR]
CODE: [CODE]
ENVIRONMENT: [ENVIRONMENT]
EXPECTED_BEHAVIOR: [EXPECTED_BEHAVIOR]

06

Salida de ejemplo

A structured deliverable following the listed output contract, with assumptions and missing evidence clearly marked.

Cómo personalizar

Replace every variable with specific, non-sensitive information. Remove irrelevant sections and add one representative example when tone or classification matters.

Errores comunes

Do not paste secrets or personal data. Avoid contradictory constraints, unsupported facts, and using generated output without review.

Notas de prueba

Editorial blueprint awaiting recorded cross-model evaluation. It is visible for review but is not labeled as tested.

Why is this blueprint not marked as tested?

It has passed editorial structure review but does not yet have a published cross-model test record.

07

Prompts relacionados